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首页> 外文期刊>Genome Integrity >Development and validation of 'AutoRIF': software for the automated analysis of radiation-induced foci
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Development and validation of 'AutoRIF': software for the automated analysis of radiation-induced foci

机译：“ AutoRIF”的开发和验证：用于自动分析辐射诱发病灶的软件

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Background The quantification of radiation-induced foci (RIF) to investigate the induction and subsequent repair of DNA double strands breaks is now commonplace. Over the last decade systems specific for the automatic quantification of RIF have been developed for this purpose, however to ask more mechanistic questions on the spatio-temporal aspects of RIF, an automated RIF analysis platform that also quantifies RIF size/volume and relative three-dimensional (3D) distribution of RIF within individual nuclei, is required. Results A java-based image analysis system has been developed (AutoRIF) that quantifies the number, size/volume and relative nuclear locations of RIF within 3D nuclear volumes. Our approach identifies nuclei using the dynamic Otsu threshold and RIF by enhanced Laplacian filtering and maximum entropy thresholding steps and, has an application 'batch optimisation' process to ensure reproducible quantification of RIF. AutoRIF was validated by comparing output against manual quantification of the same 2D and 3D image stacks with results showing excellent concordance over a whole range of sample time points (and therefore range of total RIFucleus) after low-LET radiation exposure. Conclusions This high-throughput automated RIF analysis system generates data with greater depth of information and reproducibility than that which can be achieved manually and may contribute toward the standardisation of RIF analysis. In particular, AutoRIF is a powerful tool for studying spatio-temporal relationships of RIF using a range of DNA damage response markers and can be run independently of other software, enabling most personal computers to perform image analysis. Future considerations for AutoRIF will likely include more complex algorithms that enable multiplex analysis for increasing combinations of cellular markers.
机译：背景技术现在，对辐射诱导灶（RIF）进行定量研究以研究DNA双链断裂的诱导和随后的修复已很普遍。在过去的十年中，已为此目的开发了专用于RIF自动量化的系统，但是，对于RIF的时空方面提出了更多的机械问题，RIF自动分析平台还可以量化RIF的大小/体积以及相对的三个需要单个核内RIF的三维（3D）分布。结果已经开发了基于Java的图像分析系统（AutoRIF），该系统可以量化3D核体积内RIF的数量，大小/体积和相对核位置。我们的方法使用动态Otsu阈值和RIF通过增强的Laplacian滤波和最大熵阈值步骤来识别核，并且具有“批处理优化”应用程序以确保RIF的可重复量化。通过将输出与手动量化相同2D和3D图像堆栈进行比较，对AutoRIF进行了验证，结果表明，在低LET辐射照射后的整个采样时间范围内（因此在整个RIF /核范围内），结果显示出极好的一致性。结论该高通量的自动化RIF分析系统生成的数据具有比手动获得的信息更深入，更可重复的数据，可能有助于RIF分析的标准化。特别是，AutoRIF是使用一系列DNA损伤反应标记来研究RIF时空关系的强大工具，并且可以独立于其他软件运行，从而使大多数个人计算机都可以执行图像分析。 AutoRIF的未来考虑因素可能包括更复杂的算法，这些算法可以进行多重分析以增加细胞标记的组合。

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